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  1. Abstract Background

    Countries have long been making efforts by reducing greenhouse-gas emissions to mitigate climate change. In the agreements of the United Nations Framework Convention on Climate Change, involved countries have committed to reduction targets. However, carbon (C) sink and its involving processes by natural ecosystems remain difficult to quantify.

    Methods

    Using a transient traceability framework, we estimated country-level land C sink and its causing components by 2050 simulated by 12 Earth System Models involved in the Coupled Model Intercomparison Project Phase 5 (CMIP5) under RCP8.5.

    Results

    The top 20 countries with highest C sink have the potential to sequester 62 Pg C in total, among which, Russia, Canada, USA, China, and Brazil sequester the most. This C sink consists of four components: production-driven change, turnover-driven change, change in instantaneous C storage potential, and interaction between production-driven change and turnover-driven change. The four components account for 49.5%, 28.1%, 14.5%, and 7.9% of the land C sink, respectively.

    Conclusion

    The model-based estimates highlight that land C sink potentially offsets a substantial proportion of greenhouse-gas emissions, especially for countries where net primary production (NPP) likely increases substantially and inherent residence time elongates.

     
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  2. Key Points A new semi‐analytical spin‐up (SASU) framework combines the default accelerated spin‐up method and matrix analytical algorithm SASU accelerates CLIM5 spin‐up by tens of times, becoming the fastest method to our knowledge SASU is applicable to most biogeochemical models and enables computationally costly study, for example, sensitivity analysis 
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    Free, publicly-accessible full text available August 1, 2024
  3. Abstract Large across‐model spread in simulating land carbon (C) dynamics has been ubiquitously demonstrated in model intercomparison projects (MIPs), and became a major impediment in advancing climate change prediction. Thus, it is imperative to identify underlying sources of the spread. Here, we used a novel matrix approach to analytically pin down the sources of across‐model spread in transient peatland C dynamics in response to a factorial combination of two atmospheric CO 2 levels and five temperature levels. We developed a matrix‐based MIP by converting the C cycle module of eight land models (i.e., TEM, CENTURY4, DALEC2, TECO, FBDC, CASA, CLM4.5 and ORCHIDEE) into eight matrix models. While the model average of ecosystem C storage was comparable to the measurement, the simulation differed largely among models, mainly due to inter‐model difference in baseline C residence time. Models generally overestimated net ecosystem production (NEP), with a large spread that was mainly attributed to inter‐model difference in environmental scalar. Based on the sources of spreads identified, we sequentially standardized model parameters to shrink simulated ecosystem C storage and NEP to almost none. Models generally captured the observed negative response of NEP to warming, but differed largely in the magnitude of response, due to differences in baseline C residence time and temperature sensitivity of decomposition. While there was a lack of response of NEP to elevated CO 2 (eCO 2 ) concentrations in the measurements, simulated NEP responded positively to eCO 2 concentrations in most models, due to the positive responses of simulated net primary production. Our study used one case study in Minnesota peatland to demonstrate that the sources of across‐model spreads in simulating transient C dynamics can be precisely traced to model structures and parameters, regardless of their complexity, given the protocol that all the matrix models were driven by the same gross primary production and environmental variables. 
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    Free, publicly-accessible full text available May 1, 2024